Periodic Reporting for period 3 - ASINA (Anticipating Safety Issues at the Design Stage of NAno Product Development)
Période du rapport: 2023-01-01 au 2024-02-29
Nanotechnology is a key enabling technology and has great potential for addressing societal challenges including energy supply, health care, and environment protection. Nevertheless, concerns about safety and sustainability still remain open, due to the complexity and dynamic behavior that nanomaterials show in their life-cycle exposure scenarios. In response to EU Chemicals' Strategy for promoting sustainable economy and boosting innovation for safe and sustainable chemicals, ASINA promoted SSbD nano-practices, by considering all the design for X dimensions: Functionality, Production Technologies, Economic Viability, Environmental Sustainability, Safety and Regulatory Requirements.
The ASINA project addressed several objectives aimed at increasing the confidence and implementability of the SSbD approach to nanomanufacturing. Below are the actions taken in the third reporting period (deliverables and milestones achieved) to meet the specific objectives.
D1.3 (MS10) defining characterization factors (Key Performance Factors,) and attributes (Key Performance Indicators) related to NM and NEP's functionality.
D1.4 (M10) summarising strategies applied to re(design) and optimise materials and products.
D1.5 reporting material design solutions cost-effectiveness.
D2.1 summarising NM release from NEP during the life cycle stages and the relevant exposure routes.
D2.3 (MS12) predicting NM fate and exposure levels in humans and the environment.
D2.5 (MS14) assessing intrinsic hazard through in-vitro toxicity and AOP-based biomarkers of exposure.
D2.6 (MS15) reporting results on nano-risk assessment and management.
D3.4 reporting results of field monitoring campaigns in ASINA production facilities.
D3.5 (MS13) assessing LCA impacts of ASINA production facilities.
D3.6 (MS16) reporting results and guidelines for applying Digital P-SbD solutions to production sites.
D4.2 (MS17) establishing ASINA Data Curation and Data Base.
D4.3 (MS9) designing ASINA ML Tool.
D4.4 (MS9) training, testing and validating ASINA ML Tool.
D4.5 (MS11) establishing the ASINA Expert System architecture.
D4.6 (MS18) optimising ASINA Expert System and providing guidelines for its implementation.
D5.2 (MS4) implementing and validating SbD solutions in Pilot Plants.
D5.3 involving regulatory and standardization issues.
D5.4 outlining the ASINA Roadmap ASINA.
D6.7 otlining the ASINA final business plan.
D6.8 reporting on the final stakeholder workshop
D7.2 reporting on the risk follow-up
The ASINA project addressed several objectives aimed at increasing the confidence and implementability of the SSbD approach to nanomanufacturing. Below are the actions taken in the third reporting period (deliverables and milestones achieved) to meet the specific objectives.
D1.3 (MS10) defining characterization factors (Key Performance Factors,) and attributes (Key Performance Indicators) related to NM and NEP's functionality.
D1.4 (M10) summarising strategies applied to re(design) and optimise materials and products.
D1.5 reporting material design solutions cost-effectiveness.
D2.1 summarising NM release from NEP during the life cycle stages and the relevant exposure routes.
D2.3 (MS12) predicting NM fate and exposure levels in humans and the environment.
D2.5 (MS14) assessing intrinsic hazard through in-vitro toxicity and AOP-based biomarkers of exposure.
D2.6 (MS15) reporting results on nano-risk assessment and management.
D3.4 reporting results of field monitoring campaigns in ASINA production facilities.
D3.5 (MS13) assessing LCA impacts of ASINA production facilities.
D3.6 (MS16) reporting results and guidelines for applying Digital P-SbD solutions to production sites.
D4.2 (MS17) establishing ASINA Data Curation and Data Base.
D4.3 (MS9) designing ASINA ML Tool.
D4.4 (MS9) training, testing and validating ASINA ML Tool.
D4.5 (MS11) establishing the ASINA Expert System architecture.
D4.6 (MS18) optimising ASINA Expert System and providing guidelines for its implementation.
D5.2 (MS4) implementing and validating SbD solutions in Pilot Plants.
D5.3 involving regulatory and standardization issues.
D5.4 outlining the ASINA Roadmap ASINA.
D6.7 otlining the ASINA final business plan.
D6.8 reporting on the final stakeholder workshop
D7.2 reporting on the risk follow-up
The ASINA SMM is implemented through 6 technical workpackages,
In the 2nd and 3rd reporting periods, we maximised the dissemination/communication/training efforts. The Dissemination Register was updated by the partners throughout the project. At the end of the project, we disseminated the ASINA methodology and results by presenting them at 132 events (scientific conferences, workshops, webinars, training sessions, and participation in activities organized jointly with other H2020 projects). The high quality of scientific results is now shown by 36 ISI peer reviewed papers (34 of them already published in Open Access).
In the 2nd and 3rd reporting periods, we maximised the dissemination/communication/training efforts. The Dissemination Register was updated by the partners throughout the project. At the end of the project, we disseminated the ASINA methodology and results by presenting them at 132 events (scientific conferences, workshops, webinars, training sessions, and participation in activities organized jointly with other H2020 projects). The high quality of scientific results is now shown by 36 ISI peer reviewed papers (34 of them already published in Open Access).
In period 3, ASINA definitively achieved the expected impacts and more general impacts foreseen by the call.
1) Safe-by-design approaches and tools. In ASINA, we developed and verified SbD materials and production processes passing through the implementation of a simple, robust and stepwise methodology for: i) defining the design space (design hypothesis/alternatives to be adopted matching operational/cost requirements; ii) life-cycle monitoring of design variables and p-chem properties and linking them to safety and techno-economic attributes (response functions); iii) using computational tools for combining response functions, solving the intrinsic multi-factorial challenge of SbD and identifying the best design solutions; iv) developing, integrating and validating the design solutions at pilot scale.
2) Quality workplaces in line with acceptable risk levels. Emission characterization related to both indoor and outdoor emissions was measured and worker exposure assessed by using indoor exposure models. Pollution dispersion outdoors and to the general population was also assessed by using Gaussian plume model. This gave population-attributable exposure fractions and deposition of pollutants to soil and water, used to estimate accumulation in soil and water.
3) Control and mitigate exposure after the release of NM from products. Ag intake via stratum corneum during 8-h wear time and Risk Characterisation ratios (RCRs) for different textiles and different skin types were estimated. Also, unintentional oral intake was considered, resulting the only relevant intake pathway. The potential detachment of TiO2 particles from the air purifier to indoor air was assessed and general population exposure indoors was estimated by using a reasonable worst-case exposure scenario.
4) Develop and validate low-cost techniques for risk assessment and the associated design of the required post-use monitoring. We implemented Digital Twin (DT) technology in a spray-coating plant for the production of nanostructured coatings on textiles. We tested Low-Cost Particulate Matter Sensor (LCPMS) technology for airborne particle concentration monitoring, and integrated such module within the data collection layer of the ASINA-DT.
5) Increased industrial competitiveness. Offering a practical SbD methodology mitigates the risks of industrial investments in nanomanufacturing. Red Of View company (ROV) is a clear example of this real impact, they went beyond their obligations and took advantage of ASINA tools and data to optimise and produce two cosmetic industrial-scale prototyping: antiaging (8kg) and sanitising creams (5kg), at the final aim to evaluate feasibility, time, cost, scaling factors, unpredicted results.
6) Social Impact. The increase in public trust in innovative reliable and safe scientific solutions is an excellent defence against the growing problem of "uninformed auto medicine", the spread of which is increasing and difficult to control and contain.
7) Impact on human health and environment. The implementation of ASINA methodology through the selected case studies, promoted the development and delivery of safe and sustainable solutions for the removal of chemical and biological pollutants or for decreasing detrimental effects of ageing phenomena or common infections. The impact captured consumers, employees and the environment simultaneously.
8) Impact on standardization / regulation. The ASINA SbD methodology addressed standardisation and regulatory issues as part of the innovation process proposed, taking into consideration regulatory frameworks for the two Value Chains and engaging a standardisation action during all the duration of the project that came up with the release of Standardisation Toolkit, now uploaded and usable through ASINA web-site.
Compared to the initial version of the exploitation plan, a careful revision was carried out to consolidate and better order the ASINA Key Exploitable Results (KERs). A detailed characterisation of each KERs is reported in the third periodic report (3RP). Seven commercial KERs have been selected for their potential commercial / end users exploitation, whilst four KERs were classified as "knowledge sharing".
1) Safe-by-design approaches and tools. In ASINA, we developed and verified SbD materials and production processes passing through the implementation of a simple, robust and stepwise methodology for: i) defining the design space (design hypothesis/alternatives to be adopted matching operational/cost requirements; ii) life-cycle monitoring of design variables and p-chem properties and linking them to safety and techno-economic attributes (response functions); iii) using computational tools for combining response functions, solving the intrinsic multi-factorial challenge of SbD and identifying the best design solutions; iv) developing, integrating and validating the design solutions at pilot scale.
2) Quality workplaces in line with acceptable risk levels. Emission characterization related to both indoor and outdoor emissions was measured and worker exposure assessed by using indoor exposure models. Pollution dispersion outdoors and to the general population was also assessed by using Gaussian plume model. This gave population-attributable exposure fractions and deposition of pollutants to soil and water, used to estimate accumulation in soil and water.
3) Control and mitigate exposure after the release of NM from products. Ag intake via stratum corneum during 8-h wear time and Risk Characterisation ratios (RCRs) for different textiles and different skin types were estimated. Also, unintentional oral intake was considered, resulting the only relevant intake pathway. The potential detachment of TiO2 particles from the air purifier to indoor air was assessed and general population exposure indoors was estimated by using a reasonable worst-case exposure scenario.
4) Develop and validate low-cost techniques for risk assessment and the associated design of the required post-use monitoring. We implemented Digital Twin (DT) technology in a spray-coating plant for the production of nanostructured coatings on textiles. We tested Low-Cost Particulate Matter Sensor (LCPMS) technology for airborne particle concentration monitoring, and integrated such module within the data collection layer of the ASINA-DT.
5) Increased industrial competitiveness. Offering a practical SbD methodology mitigates the risks of industrial investments in nanomanufacturing. Red Of View company (ROV) is a clear example of this real impact, they went beyond their obligations and took advantage of ASINA tools and data to optimise and produce two cosmetic industrial-scale prototyping: antiaging (8kg) and sanitising creams (5kg), at the final aim to evaluate feasibility, time, cost, scaling factors, unpredicted results.
6) Social Impact. The increase in public trust in innovative reliable and safe scientific solutions is an excellent defence against the growing problem of "uninformed auto medicine", the spread of which is increasing and difficult to control and contain.
7) Impact on human health and environment. The implementation of ASINA methodology through the selected case studies, promoted the development and delivery of safe and sustainable solutions for the removal of chemical and biological pollutants or for decreasing detrimental effects of ageing phenomena or common infections. The impact captured consumers, employees and the environment simultaneously.
8) Impact on standardization / regulation. The ASINA SbD methodology addressed standardisation and regulatory issues as part of the innovation process proposed, taking into consideration regulatory frameworks for the two Value Chains and engaging a standardisation action during all the duration of the project that came up with the release of Standardisation Toolkit, now uploaded and usable through ASINA web-site.
Compared to the initial version of the exploitation plan, a careful revision was carried out to consolidate and better order the ASINA Key Exploitable Results (KERs). A detailed characterisation of each KERs is reported in the third periodic report (3RP). Seven commercial KERs have been selected for their potential commercial / end users exploitation, whilst four KERs were classified as "knowledge sharing".